Filed by AdTheorent, Inc. pursuant to
Rule 425 under the Securities Act of 1933
and deemed filed pursuant to Rule 14a-12
under the Securities Exchange Act of 1934
Subject Company: AdTheorent, Inc.
(Commission File No. 001-40116)
The following is a transcript of the interview of James Lawson, CEO of AdTheorent, Inc. on Seeking Alpha on May 10, 2021, which references the proposed merger with MCAP Acquisition Corporation.
Intro:
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Josh Kincaid:
Welcome back to Seeking Alpha. I'm Josh Kincaid, capital markets analyst, and today interviewing CEOs. My next guest is Jim Lawson, CEO of AdTheorent. Jim, thanks for being with us at Seeking Alpha.
Jim Lawson:
Thank you for having me, Josh. It's good to be here.
Josh Kincaid:
I appreciate it. So, AdTheorent’s machine learning platform is powering its predictive targeting geo-intelligence and audience extension solutions, and connects with users through executing engaging, next level advertising campaigns, accessing only non-sensitive data and focused on the predictive value of machine learning models. Can you kind of unpack that a little bit?
Jim Lawson:
Yeah, that was a mouthful. That's a lot of information about our company in one sentence. So yeah, at the end of the day, we are a programmatic digital advertising platform and we have reimagined how digital ads can be targeted to users in a programmatic environment. We call it predictive advertising and it's new and it's transformative. We are data-driven, powered by machine learning in a way that no other DSP or programmatic digital advertiser operates. And, because of the way that we use data and don't use data, we're very privacy-forward. And, if you'd like, I could kind of unpack that a little bit, because in our space and ad tech, there's often a lot of buzzwords and rhetoric that most people don't understand kind of at face value.
So, not a lot of people realize that when you access digital content, there is an auction system taking place in the background of you accessing that content. Buyers of media, publishers and advertisers are buying and selling digital real estate. Historically, the digital ad targeting that has occurred has focused on the behavior of the user behavioral elements, behavioral advertising, mostly cookie-based retargeting where essentially, a user's personal web browsing activities are used for retargeting around the internet or licensed user IDs and profiles are used to target individuals around the internet. The sources of some of that data is murky. Sometimes it's dubious, whether it's accurate. What we have done is fundamentally different. AdTheorent predictive advertising uses machine learning and data science in a privacy-forward manner, which is not reliant on individualized cookies or user IDs for targeting. We assign predictive scores to every single impression that comes through our system. We evaluate and score over a million impressions per second or more than 87 billion per day, and then we make bidding decisions based on the predictive scores from our platform. What that means in a nutshell is when the data comes in from our publishers, our machine learning and algorithms detect whether a given impression, regardless of who the user is, is more or less likely to convert for a given advertisers KPI.
Josh Kincaid:
This is obviously more sophisticated than hashtags, and we'll get into that.
You said since 2012, you've pioneered a new way to target digital ads programmatically, without relying on user-specific personal profiles and individual data. I think that privacy is really important in the face of the movie that kind of came out against social media. So, are you a target for ESG (Environmental Social Governance)? Are you targeting those indexes and funds to expand your opportunity for investors to reach you?
Jim Lawson:
You know, we're a great target for any fund. I mean, if you're looking for a company that has a proven track record of financial performance and has created something fundamentally different, and that has a number of major strategic advantages in a marketplace that is growing at an astronomical level, we're a good company to look at. It just so happens, in 2012, I'm not going to pretend that we knew in 2012 that the state of the privacy landscape in 2021 would be what it is. I'm not going to pretend that we're that smart, but in 2012, we were creating a targeting infrastructure that took into account mobile devices. We were originally a mobile-focused business and we realized then that without cookies, how could you effectively target mobile ads? And that was when we realized that if you could incorporate the power of data science and machine learning into a bidding infrastructure and do that in real time, that you would be able to transform mobile.
We quickly realized that this same approach made a lot of sense across all screens. So we became truly omni-channel, but our original thesis was tied to mobile and not using cookies. And now, here you are in 2021 where there's a lot of reasons why consumers and businesses are pushing back against some of the abuses that have taken place in digital. There are a lot of very effective and ethical ways to target ads and cookies are not inherently bad and other IDs are not inherently bad. Sometimes they're used in bad ways. We all want the internet to be free. We don't want paywalls everywhere. We don't want Google and Facebook to continue to control all of the content out there. The open internet is a beautiful thing, and it is subsidized by advertising, but our method of targeting those ads, which makes the ads more useful to the user and better for the brands that run the campaigns. It's just a win-win situation.
Josh Kincaid:
Talk to me a little bit about the success that you've had. I want to know about key drivers for your margins over the last couple of years, you guys have had extensive post-campaign analysis. You focus on result-oriented KPIs, which I think are important. Any key performance indicators in financial services, that I work in, or pharmaceuticals, dining, travel, tourism, retail, consumer packaged goods verticals, whatever it is, is that your key to success? If not, what are your margins are your key drivers for margin?
Jim Lawson:
Yeah, so we're able to deliver. For us, it all starts with customer performance. If our customers get what they want, they're going to be happy. If they drive the KPIs, the business KPIs that they're looking for with their campaigns, they will come back. So that's where we start. We need to deliver -- every conversation with our customer starts with what business outcome are you trying to achieve? And by that, I don't mean clicks. I don't mean views. I don't mean video views. What business outcome are you trying to sell? Credit card signups? Are you trying to sell insurance? Are you trying to sell, are you trying to get users to visit stores or restaurants or online sales? Whatever that is, that is our end goal for our machine learning models and that's what we optimize towards. The way that we are efficient and have built a profitable business is that we have a platform that is capable of doing that performance in a much more efficient manner.
We can find conversions in the ecosystem, in the digital ecosystem. We can find conversions much more efficiently than any other platform. Again, we're not reliant on an assumptions-driven, cookie-based, or ID-based targeting method. By using machine learning, which essentially looks at conversion activity from the past; so, we will look at of the credit card conversions or of the credit card signups that occurred in the past, for example, if that's what the client's trying to drive, what were the non-personally identifiable attributes associated with those impressions when those conversions occurred? And then, our machine learning model will optimize towards that. We bid on less than one tenth of one percent of the impressions that come through our system. So we're very efficient. We can find that needle in a haystack without a lot of waste, and that makes us more efficient.
We also have a number of algorithms, and we use machine learning in our platform to minimize a lot of the challenges, or mitigate a lot of the challenges that cause waste for other platforms with respect to things like fraud and purchasing fraudulent inventory or purchasing inventory that is not brand safe. And ultimately clients rightly don't want to pay for that, or impressions that are not viewable, properly viewable. And then you essentially are wasting money on inventory that's not providing any value to your customer. So, we can also use machine learning and data science to be better there. For us, it's all about value and then using the tools and the superior tools and the superior benefits that machine learning provide as opposed to the status quo method, which is licensing third-party audience segments from other companies that have dubious validity and then basing your entire targeting infrastructure on that. Our method’s just more efficient and by satisfying customers and driving their performance in an efficient manner, we've built a really strong business over the last 10 years. And we're going to be north of 30 million in EBITDA this year, and our revenues are going to be over $150 million in 2021. With all of our metrics, there's never been more demand for what we're doing.
Josh Kincaid:
I think you guys raised $168 million for the research and development of the algorithm. So, pardon me if I kind of dumb this down, but essentially with the bidding, are you essentially saying it's kind of like Waze? Where it's going to get you what you want, but the fastest, most efficient manner?
Jim Lawson:
Well, I don't know exactly what they do, but that's a very good way of putting it. We’re using, in the same way that Waze is using data to inform decisioning, that's what we're doing. And we're very excited to have Palantir involved in our round as well, because they are going to help us leverage some of our data infrastructure and be able to be more nimble with data and be able to use data more effectively and efficiently, because for us, again, we're not a data company. We don't compile data. We don't compile user profiles. We don't maintain information about users. We're just acting in real time when an opportunity to serve an ad presents itself to one of our advertisers through our platform. We analyze that in real-time, and we have a lot of data that's not tied back to an individual. And for us, machine learning can tell us whether it's a smart way to go for a given campaign.
Josh Kincaid:
Tell me a little bit about the SPAC. Not a lot of people are, they've heard about it maybe they're not familiar with it. I think it's an interesting option, a way to go public. So tell us a little bit about going public and why you chose this SPAC deal instead of a traditional IPO.
Jim Lawson:
Yeah, so that's a great question. We realized that it was time given the demand for what we were doing. We realized that it was time for AdTheorent to get on a bigger stage. We needed to get out into a bigger marketplace, whether through some sort of strategic combination or going public. Ultimately, we decided that being in the public markets was the answer for us and was going to give us the greatest opportunity to realize the value that we’re capable of creating given our platform. We actually were very fortunate to be involved with our SPAC sponsor Monroe Capital for the last five years. They've been actually a stakeholder in our company for the last five years. They were the primary lender in the transaction that we did with private equity firm HIG in 2016.
So, we've been working with Monroe Capital for five years and we know them well and we trust them. And they really believe in our vision for our company and they've been big supporters. So, when we learned that they had a SPAC and they've been successful with their other SPACs, one of them being Repay, I think, which is in the top ten SPAC performers. That, coupled with our experience with them and the efficiencies that in getting to market quicker that a SPAC represented for us, it seemed like the right answer. There were a number of options. We were lucky to have a number of really good strategic options. And we chose to go this route because it was the most efficient way to be a public company and maintain our partnership with Monroe and continue our vision forward. But unlike a lot of SPACs, we all read about companies that are going public and different ways that they do it, we’re not an experimental flying toaster or something. We're a business that has proven our business model over a long period of time. We're profitable with $30 million in EBITDA and $150 million in revenue. So, we stand out a little bit from some of those companies. But once we get public, we’re public and we're really excited about it.
Josh Kincaid:
If somebody is making a flying toaster, they can go to you and get exactly what they need. The capital raised from the SPAC merger, that helped you guys fund growth plans, including international expansion, acquisition. Maybe you can elaborate on how that's working out. You also mentioned that the company lists the growth of connected television advertising spend as an opportunity that's in its early stages. Wondering if that's still true and how you're taking advantage of that.
Jim Lawson:
So we obviously haven't spent any of this money yet because we haven't closed our deal, which will occur in the fourth quarter, but we are very excited by the opportunity to have this extra growth capital and the partnerships that we will bring to the table post-closing. There are a number of immediate ways to organically accelerate our growth. One of them is CTV, as you mentioned. Streaming services like Hulu are the fastest growing sectors in digital. As you know, traditional TV dollars are shifting to digital -- close to $45 billion in 2021 and $53 billion, I believe, in 2022. And we use our machine learning algorithms and platform within the CTV context to drive performance-based outcomes there as well. With limited investment in 2021, our CTV revenues are going to be approximately $40 million, which is about a 300% growth rate for us year-over-year.
We believe that with additional investment in our CTV offering both in terms of the scale and the inventory and some of the additional measurement and attribution and other value-added services that we provide, that we can really continue to grow CTV and even outpace materially the segment growth, and the segment is growing at a very rapid pace. There are a number of other areas that we believe we can accelerate our growth organically just by doing more of what we're doing. That includes continuing to invest in our verticalization. I've spoken a lot about our core platform capabilities, which is machine learning and driving performance using machine learning. But on top of that, there are different needs that different verticals and different businesses have. And we have invested a lot, again, we've been a small business, we're private equity-owned and we've been very focused on profitability and being efficient, which we will continue to do.
We’re old-fashioned in the sense that we like to make more money than we spend and that that's not going to change, but we also believe that with more investment, our banking and financial services and insurance division of our business has really grown. And that's because we leaned into it about a year ago and really invested in differentiation to those customers, including knowing about their data challenges and knowing, for example, in regulated banking and credit extension products, there are limits to the data that you can use for ad targeting. And that's all factored and incorporated into our modeling. So, we're able to drive very custom banking and financial services solutions because we know the data challenges they have, we know the types of KPIs they're trying to drive, and we've built very specific businesses for them.
So, we're not going into the world's most sophisticated advertiser bank and pitching the same thing that we would pitch to an auto manufacturer. We're investing more in those solutions you always gotta be showing up to the table with value and providing new things. And the more capital we have, we have a tech team we're so lucky to have a tech and product team and data science team that is always coming up with new ways that we can deploy our machine learning platform. And with more resources, we can hire more really smart people to join our team and help us.
Josh Kincaid:
What are you excited about coming up? Like we're just surpassing the first half of 2021. I'm wondering about the contributions that you guys are going to have for growth and enterprise valuation. What are you excited about as we approach the close of the SPAC?
Jim Lawson:
We couldn't be more excited about getting out there and utilizing this bigger stage, educating more customers in the digital marketplace about programmatic digital advertising powered by machine learning. It is a seat change. It's transformational. There are many advertisers that don't know what we do is even possible, and we want to get in front of them. And we want to tell them about using machine learning powered predictive advertising with AdTheorent and the benefits of that. As the cookie and as other individualized IDs are less prevalent in digital due to some of the changes that Google is making and Apple are making, which are tightening availability in the not-too-distant future of the availability of cookies in the Chrome browser and the ability to use Apple device IDs in ad targeting. So as those individualized IDs go more towards the past, our solution becomes even more relevant and we don't need those IDs to target, as I mentioned.
So, we're very excited about, again, more education. We're having an education series with our customers and telling them about addressability and the future and how AdTheorent can be a big part of that. So, when we get through the closing we’ll be very excited to go out and pursue the ambitious product and tech roadmap that we have, and then just go capture more topline revenue while doing so in an efficient manner. We're a rule of 50 company. We have profit, EBITDA margins and revenue margins that are quite impressive. And we want to go out into a bigger market and sell our products and services.
Josh Kincaid:
Have you guys at AdTheorent seen a post-pandemic shift in the way that you have to target consumers? For example, before the pandemic, was it majority mobile as people were searching? And is it now desktop as people are working from home? I'm just curious pre- and post-pandemic, what are some of the behavioral changes that the machine has learned and is engaging in now?
Jim Lawson:
Yeah, that's a great question. We learned a lot during the pandemic. In the very early stages of the pandemic, like everybody in the world, we weren't sure what was coming. We learned a lot about our business. We learned a lot about our customers during that time. And in the pandemic, there was the beginning period where essentially the economy shut down and everybody was kind of like, you know, you spend a lot of time, drinking and figuring out what's coming next, like “is this the end of the world?” And then I think everybody kind of realized that it was going to be okay. And our advertisers pivoted quickly towards the version of their products and services that were going to be least impacted by the pandemic.
And then frankly, many advertisers, and ourselves I would include in that group, saw opportunity. The fact that we were all locked in our basements meant that a lot of us were spending a lot more time online. One of the main changes that we saw in our campaigns was the shift to online transactions. Whereas in the past we might've had, for example, quick service restaurants, where we would have campaigns focused on driving physical visitation. Those campaigns we pivoted towards online ordering, and we worked with our customers to update their strategies, to make them more COVID-proof. And we wound up growing some industry verticals that we didn't have prior to the pandemic, or that we didn't have the same depth with, for example, our government and healthcare verticals. We have been working with some great state departments of health to get the word out on COVID information and vaccine information.
And we've done a really good job partnering with those state and local governments to get the word out and that's been a growth area for us. Now that the pandemic is, you know, we see the light at the end of the tunnel, we benefit from now having more vertical expertise. Our financial services and banking and insurance, I mean, the world continues to move on. You still need insurance, you still need bank accounts. So those verticals were, just after a very relatively short period of disruption, we came back roaring and so we're really excited about that. And now we have a number of new verticals like government and lotteries, and a number of other verticals that have come back that we didn't even know we had prior to the pandemic and our team stepped up as well. We realized that in a tighter advertising market advertisers want to focus their spend on the platforms that can prove return on ad spend.
And that's our sweet spot. So, a lot of platforms in digital and in advertising generally are stuck in the past where you're focused on the number of impressions that you're going to deliver, or the scale of the ads that you're going to send out and not on the return on that, that comes back to the advertiser. What is the measurable return on investment that the advertiser got? And that's what we specialize in. And during the pandemic, we saw advertisers really focusing their budgets on partners like us, where there was a proven track record of performance over a large period of time. And that for us, provides us a lot of confidence going forward that we can get through anything.
Josh Kincaid:
Do you think with respects to data aggregation that 2020 was a golden year? But that should also maybe have an asterisk next to it with everyone's spending online, there was a lot less cash in the system, which would in theory, give you access to a lot more data than you've ever seen. However, when people go back to “normal” and spend cash, you'll have in theory, less access to that data, is that going to affect or skew 2020?
Jim Lawson:
Well, we don't really access that type of data. The data that we get, so you go to a publication online and that renders if there's an opportunity to serve an ad on that publication that will come into our platform and all the other ad platforms, and then the type of information that we access and use in that example would be, what is the name of that publication? What are the keywords in the URL? What is the location of this ad request? Where was the user when that request came in? What is the operating system of the phone? How big is the creative? How old is the phone? What is the language setting on the phone? Are there keyword learnings from the content of the page? And those types of things.
So that's what informs, there's up to 200 of those types of attributes that we ingest and use in our models, but we don't really tap into some of those other data points. We can work with customers and ask them too. For example, a large retailer might have a customer list and they might come to us and say, “we would like to target our customer list in the digital world.” And we can help them do that. Or they could say, “This is our customer list. We don't want to target them. We want to target new customers.” And that's one of the things we call predictive prospecting, which is again, our sweet spot, casting a wide net and letting the machine optimize closer towards ‘what are the attributes that are most valuable?’ And it's not going to be individualized IDs, because those are not common attributes among larger groups.
It could be things that you might not even think make any sense. It could be the weather, it could be the weather, the location, and the operating system for whatever reason might drive a lot more performance for a given product or service at a given time. So, it doesn't always necessarily make sense, but the more data you have the better, and it doesn't need to be Facebook. We all read about them using -- you have a health app, they know your both blood pressure and to the extent that ads are being sent or used on those types of things. It's obviously not what we do. I believe we represent an alternative to that. And a lot of people think that social is where most advertising goes or should go, but there was an eMarketer report that the amount of time people spend on social, most consumers spend on social is like 15% or slightly less than 15% of their digital time.
So, there's a lot of time that consumers are spending online in different places, shopping, looking for news, in the open internet, on different/their favorite apps, etcetera. It's not just all happening in social. It's just so happens that social knows everything about you, all about your secrets and your emails and everything. And they like keeping a strong control over that ecosystem, but that's not where we play, we're in the open internet. And we believe that there's a great future for that. And I think it's a more customer friendly place to advertise.
Josh Kincaid:
What can you tell us about your last quarter’s earnings?
Jim Lawson:
We’re feeling really good. Our second quarter is quite strong. We're coming in right where we wanted to be, ahead of our personal expectations. The marketplace, through the first half of the year, we have a number of exciting metrics to report. Through the first half of the year, our growth is tracking at 105% over last year. With the first quarter being 34% and the second quarter being over 70%. That reflects a number of positive things that are happening for us. Our brand direct sales are up 80%, and that's where we're just working directly with brands. Our large partnership commitment increases are up 60%. And that's where we partner with agencies, and we work with them, and we have understandings about how much money they think they're going to spend with us for the year. And those commitments in 2021 in the first half of the year are up 60% relative to last year. Our bookings are up nicely 50%, our CTV as I mentioned earlier is up 300%, our video generally is up 40%. So, our first half is shaping up to be a very strong, strong period of performance for us. There's a $90 billion opportunity in digital media for 2021, growing at 17.5%. And we believe our growth rate will exceed that growth rate. And we couldn't be more excited about the second half of the year. We have a number of things in our roadmap, both from a product perspective, the tech perspective, and just different things that we're going to get out in front of customers. So, very bright forecast for us. We're very excited about the future.
Josh Kincaid:
If you're artificial intelligence and machine learning algorithm had predictive analytics on your future stock, what do you think it would say?
Jim Lawson:
Oh, wow, that's a good question. You know what the real answer is? The real answer to that is, it would say it doesn't have data. In other words, the way our models learn is they learn from performance, and they learn from the actual data in the real world. So, our models might not be useful because we haven't started trading yet, but we feel good. We feel like as a business that really has a lot of respect for fundamentals and maintaining a disciplined approach to the balance between growth and investing in the business and being careful with waste and just making sure that we're very prudent with how we grow our business and making sure that our vendor relationships are the right agreements and that we don't have redundancies.
We think that we're really well-positioned to perform well in the public markets. We're not going to look at it every day and decide our self-worth based on whether the stock price went up a couple points here and there, because we believe in the long-term strategy. We believe that quarter-over-quarter-over quarter, year-over-year, we have something very special. We have something very valuable that's worth investing in, that's worth being a part of. And we have a lot of very smart partners. That’s a great question that our data scientists will probably love to jump on at some point. And maybe I can come back and talk to you when we have some trading data, because the stock market's a very interesting thing, and there's a lot of data out there, so I'm sure they'll be running algorithms that I won't even know about. But that's a great question.
Josh Kincaid:
I’m sure FINRA and the SEC would prefer it that way as well. Regulatory authorities would prefer you to wait until you're public before we start talking about that anyways. Where can they find you though? You're going to be going public later this year. Do you have a stock ticker symbol yet? What is your website? Where can people find you? And where can potential investors buy into your equity?
Jim Lawson:
Yeah, that's a great question. Our ticker symbol, I won't say it now because I think it's like 99%, but I don't think we have it confirmed yet from the NASDAQ. You can obviously find us and learn about our business at adtheorent.com, which is our corporate website and a lot of great information there about us, including a link to the M Cap sponsor with which we've just merged. And that publicly traded ticker symbol, M Cap Acquisition Corp is linkable from our website. There's a banner at the top of our page. We're excited to announce on our website. We'd love folks to reach out and learn more about AdTheorent, read about our solutions. We're always interested obviously, if there's any new customers out there, always interested in talking to them. There's going to be more information coming about the stock, a ticker symbol and all that later when we have that locked down with the lawyers.
Josh Kincaid:
Sounds good. All right. I think with that, we're going to wrap this one up. I want to thank my guest Jim Lawson, CEO of AdTheorent. Jim, thanks for being with us at Seeking Alpha.
Jim Lawson:
Thanks so much. I appreciate the opportunity.
Josh Kincaid:
You're welcome. I'm Josh Kincaid. This is Seeking Alpha. Don't forget to like, share, and subscribe.
IMPORTANT INFORMATION FOR SHAREHOLDERS AND INVESTORS
In connection with the proposed merger with AdTheorent, Inc. (“AdTheorent”), MCAP Acquisition Corporation (“MCAP”) intends to file a registration statement on Form S-4 with the Securities and Exchange Commission (the “SEC”) that will include a proxy statement/prospectus of MCAP, and will file other documents regarding the proposed transaction with the SEC. Before making any voting or investment decision, investors and stockholders of AdThoreant and MCAP are urged to carefully read the entire registration statement and proxy statement/prospectus, when they become available, and any other relevant documents filed with the SEC, as well as any amendments or supplements to these documents, because they will contain important information about AdTheorent, MCAP and the business combination transaction. The documents filed by MCAP with the SEC may be obtained free of charge at the SEC’s website at www.sec.gov, or by directing a request to MCAP Acquisition Corporation, 311 South Wacker Drive, Suite 6400, Chicago, Illinois 60606.
Participants in the Solicitation
MCAP, AdTheorent and certain of their respective directors and executive officers may be deemed participants in the solicitation of proxies from MCAP’s stockholders with respect to the business combination. A list of the names of those directors and executive officers and a description of their interests in MCAP will be included in the proxy statement/prospectus for the proposed business combination when available at www.sec.gov. Information about MCAP’s directors and executive officers and their ownership of MCAP common stock is set forth in MCAP’s prospectus, dated February 25, 2021, as modified or supplemented by any Form 3 or Form 4 filed with the SEC since the date of such filing. Other information regarding the interests of the participants in the proxy solicitation (including AdTheorent and its members and executive officers) will be included in the proxy statement/prospectus pertaining to the proposed business combination when it becomes available. These documents can be obtained free of charge as indicated above.